prysm.detector¶

Detector-related simulations.

class prysm.detector.Detector(pitch_x=None, pitch_y=None, pixel='rectangle', resolution=(1024, 1024), nbits=16, framebuffer=10)¶

Bases: object

Model of a image sensor.

capture(convolvable)¶

Sample a convolvable, mimics capturing a photo of an oversampled representation of an image.

Parameters: convolvable (prysm.Convolvable) – a convolvable object
Returns: a new convolvable object, as it would be sampled by the detector
Return type: prysm.convolvable
Raises: ValueError – if the convolvable would have to become supersampled by the detector; this would lead to an inaccurate result and is not supported

save_image(path, which='last')¶

Save an image captured by the detector.

Parameters

path (string) – path to save the image to
which (string or int) – if string, “first” or “last”, otherwise index into the capture buffer of the camera.

Raises

ValueError – bad target frame to save; should always be the a valid int < buffer_depth

show_image(which='last', fig=None, ax=None)¶

Show an image captured by the detector.

Parameters

which (string or int) – if string, “first” or “last”, otherwise index into the capture buffer of the camera
fig (matplotlib.figure.Figure, optional) – Figure containing the plot
ax (matplotlib.axes.Axis, optional) – Axis containing the plot

Returns

fig (`matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot

pitch¶: 1D pixel pitch - minimum of x/y pitches.

fill_factor_x¶: Fill factor in the X axis.

fill_factor_y¶: Fill factor in the Y axis.

fill_factor¶: 1D fill factor – minimum of x/y fill factors.

fs¶: Sampling frequency in cy/mm.

nyquist¶: Nyquist frequency in cy/mm.

last¶: Last frame captured.

class prysm.detector.OLPF(width_x, width_y=None, sample_spacing=0, samples_x=None, samples_y=None)¶

Bases: prysm.convolution.Convolvable

Optical Low Pass Filter.

analytic_ft(x, y)¶

Analytic fourier transform of a pixel aperture.

Parameters

x (numpy.ndarray) – sample points in x axis
y (numpy.ndarray) – sample points in y axis

Returns

2D numpy array containing the analytic fourier transform

Return type

numpy.ndarray

center_x¶: Center “pixel” in x.

center_y¶: Center “pixel” in y.

conv(other)¶

Convolves this convolvable with another.

Parameters: other (Convolvable) – A convolvable object
Returns: a convolvable object
Return type: Convolvable

Notes

If self and other both have analytic Fourier transforms, no math will be done and the aFTs are merged directly.

If only one of self or other has an analytic Fourier transform, the output grid will be defined by the object which does not have an analytic Fourier transform.

If neither has an analytic transform, the output grid will: - span max(self.support, other.support) - have sample spacing min(self.sample_spacing, other.sample_spacing)

This ensures the signal remains Nyquist sampled and (probably) doesn’t expand beyond the extent of the output window. The latter condition will be violated when two large convolvables are convolved.

copy()¶: Return a (deep) copy of this instance.

deconv(other, balance=1000, reg=None, is_real=True, clip=False, postnormalize=True)¶

Perform the deconvolution of this convolvable object by another.

Parameters

other (Convolvable) – another convolvable object, used as the PSF in a Wiener deconvolution
balance (float, optional) – regularization parameter; passed through to skimage
reg (numpy.ndarray, optional) – regularization operator, passed through to skimage
is_real (bool, optional) – True if self and other are both real
clip (bool, optional) – clips self and other into (0,1)
postnormalize (bool, optional) – normalize the result such that it falls in [0,1]

Returns

a new Convolable object

Return type

Convolvable

Notes

See skimage: http://scikit-image.org/docs/dev/api/skimage.restoration.html#skimage.restoration.wiener

static from_file(path, scale)¶

Read a monochrome 8 bit per pixel file into a new Image instance.

Parameters

path (string) – path to a file
scale (float) – pixel scale, in microns

Returns

a new image object

Return type

Convolvable

plot_slice_xy(axlim=20, lw=3, zorder=3, fig=None, ax=None)¶

Create a plot of slices through the X and Y axes of the PSF.

Parameters

axlim (float or int, optional) – axis limits, in microns
lw (float, optional) – line width
zorder (int, optional) – zorder
fig (matplotlib.figure.Figure, optional) – Figure to draw plot in
ax (matplotlib.axes.Axis) – Axis to draw plot in

Returns

fig (matplotlib.figure.Figure, optional) – Figure containing the plot
ax (matplotlib.axes.Axis, optional) – Axis containing the plot

renorm()¶: Renormalize so that the peak is at a value of unity.

sample_spacing¶: center-to-center sample spacing.

samples_x¶: Number of samples in the x dimension.

samples_y¶: Number of samples in the y dimension.

save(path, nbits=8)¶

Write the image to a png, jpg, tiff, etc.

Parameters

path (string) – path to write the image to
nbits (int) – number of bits in the output image

shape¶: Proxy to phase or data shape.

show(xlim=None, ylim=None, interp_method=None, power=1, show_colorbar=True, fig=None, ax=None)¶

Display the image.

Parameters

xlim (iterable, optional) – x axis limits
ylim (iterable,) – y axis limits
interp_method (string) – interpolation technique used in display
power (float) – inverse of power to stretch image by. E.g. power=2 will plot img ** (1/2)
show_colorbar (bool) – whether to show the colorbar or not.
fig (matplotlib.figure.Figure, optional:) – Figure containing the plot
ax (matplotlib.axes.Axis, optional:) – Axis containing the plot

Returns

fig (matplotlib.figure.Figure, optional:) – Figure containing the plot
ax (matplotlib.axes.Axis, optional:) – Axis containing the plot

show_fourier(freq_x=None, freq_y=None, interp_method='lanczos', fig=None, ax=None)¶

Display the fourier transform of the image.

Parameters

interp_method (string) – method used to interpolate the data for display.
freq_x (iterable) – x frequencies to use for convolvable with analytical FT and no data
freq_y (iterable) – y frequencies to use for convolvable with analytic FT and no data
fig (matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot

Returns

fig (matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot

Notes

freq_x and freq_y are unused when the convolvable has a .data field.

size¶: Proxy to phase or data size.

slice_x¶

Retrieve a slice through the X axis of the phase.

Returns

self.unit (numpy.ndarray) – ordinate axis
slice of self.phase or self.data (numpy.ndarray)

slice_y¶

Retrieve a slice through the Y axis of the phase.

Returns

self.unit (numpy.ndarray) – ordinate axis
slice of self.phase or self.data (numpy.ndarray)

support¶: Width of the domain.

support_x¶: Width of the domain in X.

support_y¶: Width of the domain in Y.

class prysm.detector.PixelAperture(width_x, width_y=None, sample_spacing=0, samples_x=None, samples_y=None)¶

Bases: prysm.convolution.Convolvable

The aperture of a rectangular pixel.

analytic_ft(x, y)¶

Analytic fourier transform of a pixel aperture.

Parameters

x (numpy.ndarray) – sample points in x axis
y (numpy.ndarray) – sample points in y axis

Returns

2D numpy array containing the analytic fourier transform

Return type

numpy.ndarray

center_x¶: Center “pixel” in x.

center_y¶: Center “pixel” in y.

conv(other)¶

Convolves this convolvable with another.

Parameters: other (Convolvable) – A convolvable object
Returns: a convolvable object
Return type: Convolvable

Notes

If self and other both have analytic Fourier transforms, no math will be done and the aFTs are merged directly.

If only one of self or other has an analytic Fourier transform, the output grid will be defined by the object which does not have an analytic Fourier transform.

If neither has an analytic transform, the output grid will: - span max(self.support, other.support) - have sample spacing min(self.sample_spacing, other.sample_spacing)

This ensures the signal remains Nyquist sampled and (probably) doesn’t expand beyond the extent of the output window. The latter condition will be violated when two large convolvables are convolved.

copy()¶: Return a (deep) copy of this instance.

deconv(other, balance=1000, reg=None, is_real=True, clip=False, postnormalize=True)¶

Perform the deconvolution of this convolvable object by another.

Parameters

other (Convolvable) – another convolvable object, used as the PSF in a Wiener deconvolution
balance (float, optional) – regularization parameter; passed through to skimage
reg (numpy.ndarray, optional) – regularization operator, passed through to skimage
is_real (bool, optional) – True if self and other are both real
clip (bool, optional) – clips self and other into (0,1)
postnormalize (bool, optional) – normalize the result such that it falls in [0,1]

Returns

a new Convolable object

Return type

Convolvable

Notes

See skimage: http://scikit-image.org/docs/dev/api/skimage.restoration.html#skimage.restoration.wiener

static from_file(path, scale)¶

Read a monochrome 8 bit per pixel file into a new Image instance.

Parameters

path (string) – path to a file
scale (float) – pixel scale, in microns

Returns

a new image object

Return type

Convolvable

plot_slice_xy(axlim=20, lw=3, zorder=3, fig=None, ax=None)¶

Create a plot of slices through the X and Y axes of the PSF.

Parameters

axlim (float or int, optional) – axis limits, in microns
lw (float, optional) – line width
zorder (int, optional) – zorder
fig (matplotlib.figure.Figure, optional) – Figure to draw plot in
ax (matplotlib.axes.Axis) – Axis to draw plot in

Returns

fig (matplotlib.figure.Figure, optional) – Figure containing the plot
ax (matplotlib.axes.Axis, optional) – Axis containing the plot

renorm()¶: Renormalize so that the peak is at a value of unity.

sample_spacing¶: center-to-center sample spacing.

samples_x¶: Number of samples in the x dimension.

samples_y¶: Number of samples in the y dimension.

save(path, nbits=8)¶

Write the image to a png, jpg, tiff, etc.

Parameters

path (string) – path to write the image to
nbits (int) – number of bits in the output image

shape¶: Proxy to phase or data shape.

show(xlim=None, ylim=None, interp_method=None, power=1, show_colorbar=True, fig=None, ax=None)¶

Display the image.

Parameters

xlim (iterable, optional) – x axis limits
ylim (iterable,) – y axis limits
interp_method (string) – interpolation technique used in display
power (float) – inverse of power to stretch image by. E.g. power=2 will plot img ** (1/2)
show_colorbar (bool) – whether to show the colorbar or not.
fig (matplotlib.figure.Figure, optional:) – Figure containing the plot
ax (matplotlib.axes.Axis, optional:) – Axis containing the plot

Returns

fig (matplotlib.figure.Figure, optional:) – Figure containing the plot
ax (matplotlib.axes.Axis, optional:) – Axis containing the plot

show_fourier(freq_x=None, freq_y=None, interp_method='lanczos', fig=None, ax=None)¶

Display the fourier transform of the image.

Parameters

interp_method (string) – method used to interpolate the data for display.
freq_x (iterable) – x frequencies to use for convolvable with analytical FT and no data
freq_y (iterable) – y frequencies to use for convolvable with analytic FT and no data
fig (matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot

Returns

fig (matplotlib.figure.Figure) – Figure containing the plot
ax (matplotlib.axes.Axis) – Axis containing the plot

Notes

freq_x and freq_y are unused when the convolvable has a .data field.

size¶: Proxy to phase or data size.

slice_x¶

Retrieve a slice through the X axis of the phase.

Returns

self.unit (numpy.ndarray) – ordinate axis
slice of self.phase or self.data (numpy.ndarray)

slice_y¶

Retrieve a slice through the Y axis of the phase.

Returns

self.unit (numpy.ndarray) – ordinate axis
slice of self.phase or self.data (numpy.ndarray)

support¶: Width of the domain.

support_x¶: Width of the domain in X.

support_y¶: Width of the domain in Y.

prysm.detector.pixelaperture_analytic_otf(width_x, width_y, freq_x, freq_y)¶

Analytic MTF of a rectangular pixel aperture.

Parameters

width_x (float) – x diameter of the pixel, in microns
width_y (float) – y diameter of the pixel, in microns
freq_x (numpy.ndarray) – x spatial frequency, in cycles per micron
freq_y (numpy.ndarray) – y spatial frequency, in cycles per micron

Returns

MTF of the pixel aperture

Return type

numpy.ndarray

prysm.detector.bindown(array, nsamples_x, nsamples_y=None, mode='avg')¶

Bin (resample) an array.

Parameters

array (numpy.ndarray) – array of values
nsamples_x (int) – number of samples in x axis to bin by
nsamples_y (int) – number of samples in y axis to bin by. If None, duplicates value from nsamples_x
mode (str, {‘avg’, ‘sum’}) – sum or avg, how to adjust the output signal

Returns

ndarray binned by given number of samples

Return type

numpy.ndarray

Notes

Array should be 2D. TODO: patch to allow 3D data.

If the size of array is not evenly divisible by the number of samples, the algorithm will trim around the border of the array. If the trim length is odd, one extra sample will be lost on the left side as opposed to the right side.

Raises: ValueError – invalid mode

prysm.detector.bindown_with_units(px_x, px_y, source_spacing, source_data)¶

Perform bindown, returning unit axes and data.

Parameters

px_x (float) – pixel pitch in the x direction, microns
px_y (float) – pixel pitch in the y direction, microns
source_spacing (float) – pixel pitch in the source data, microns
source_data (numpy.ndarray) – ndarray of regularly spaced data

Returns

ux (numpy.ndarray) – 1D array of sample coordinates in the x direction
uy (numpy.ndarray) – 1D array of sample coordinates in the y direction
data (numpy.ndarray) – binned-down data

prysm.detector¶

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